The ability to express emotion through speech is an essential element of human communication, yet individuals with speech impairments who rely on speech-generating devices to communicate are often deprived of this ability. Current speech-generating devices offer at most a limited number of expressive speech modes (e.g., a happy voice or a sad voice), and even when those are provided, they are often not perceived by listeners in the intended way. The proposed project aims to remedy this unfortunate situation by enhancing the rule-based Synfonica text-to-speech system with the ability to accurately convey a broad range of emotional states. The approach to be tested centers on a set of expressive speech meta-parameters that collectively describe the higher-level characteristics of the speech output required for conveying the intended emotion for a given utterance. Examples of such meta-parameters include speaking rate, pitch range, and degree of breathiness. The text-to-speech rules will implement the complex mapping from meta-parameter values to the relevant lower-level acoustic parameter values used by a synthesizer to produce the final speech waveform. Examples of such acoustic parameters are the fundamental frequency of voicing, formant frequencies, and voicing amplitude. The Phase I project aims to test the feasibility of this approach by enhancing the Synfonica system to convey four emotions-elation, sadness, and two flavors of anger (hot anger and cold anger)-on a restricted set of utterance types. A set of perceptual tests will be conducted to determine the extent to which listeners recognize the intended emotions in the synthesized speech. If successful, the Phase I project will lay the groundwork for providing users of speech-generating devices with the means to effectively convey their emotional states through speech. It also will further scientific knowledge regarding the perceptual cues used by listeners in gauging a speaker's emotional state.